Method and apparatus for improved sampling resolution in X-ray imaging systems

ABSTRACT

The present invention pertains to an apparatus and method for X-ray imaging wherein a radiation source comprising rows of discrete emissive locations can be positioned such that these rows are angularly offset relative to rows of sensing elements on a radiation sensor. A processor can process and allocate responses of the sensing elements in appropriate memory locations given the angular offset between source and sensor. This manner of allocation can include allocating the responses into data rows associated with unique positions along a direction of columns of discrete emissive locations on the source. Mapping coefficients can be determined that map allocated responses into an image plane.

CROSS REFERENCE TO RELATED APPLICATION

This application is a Continuation Application of the commonly-ownedU.S. patent application Ser. No. 13/738,614, U.S. Pat. No. 9,217,719,filed Jan. 10, 2013, by A. Lowell et al., and entitled “Method andApparatus for Improved Sampling Resolution in X-Ray Imaging Systems,”which is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention pertains to X-ray imaging systems. The presentinvention pertains more specifically to X-ray imaging systems utilizingsources having a plurality of discrete emissive locations.

BACKGROUND

Point-source X-ray imaging systems currently account for the greatestportion of medical X-ray imaging systems in the United States.Point-source X-ray imaging systems comprise an X-ray radiation sourcesuch as an X-ray tube that emits X-rays from a single discrete locationor window. While point-systems have achieved a relatively high level ofimage resolution and imaging speed, they are limited by an unfavorablesignal-to-noise ratio related to the position of the patient relative tothe source and detector and provide data sufficient only for flat, e.g.two-dimensional, images.

X-ray imaging systems have been developed that address these latter twodeficiencies. See for example U.S. Pat. No. 5,729,584 entitled “ScanningBeam X-Ray Imaging System,” issued to Moorman et al. In contrast to apoint-source imaging system, this type of imaging systems utilizes anX-ray source having a plurality of discrete emissive locations on itsface and a relatively small detector. The geometry of this type ofimaging system both improves signal-to-noise ratios by decreasing thenumber of scattered X-ray photons collected and provides sufficient datato reconstruct a range of planes between the source and detector.

However, the spatial resolution and image fidelity provided by thesesystems can vary from plane to plane, and can range from beingcompetitive with or better than advanced point-source systems and beingquite poor. Embodiments of the present invention provide a method andapparatus of improving the resolution and image fidelity of suchsystems.

SUMMARY

The present invention pertains to an apparatus and method for X-rayimaging wherein a radiation source comprising rows of discrete emissivelocations can be positioned such that these rows are angularly offsetrelative to rows of sensing elements on a radiation sensor. The angularoffset can be less than 90 degrees or less than 5 degrees, or maydisplace a sensing element by a length equal to an integer number ofsensing elements, including one, two, or three sensing elements. Aprocessor can process and allocate responses of the sensing elementsinto appropriate memory locations given the angular offset betweensource and sensor. This manner of allocation can include allocating theresponses into data rows associated with unique positions along thedirection of columns of discrete emissive locations on the source.Mapping coefficients can be determined that map allocated responses intoan image plane. Responses can be mapped along a first dimension,aggregated, and then mapped along the second dimension, or may be mappeddirectly into an image plane.

These and other objects and advantages of the various embodiments of thepresent invention will be recognized by those of ordinary skill in theart after reading the following detailed description of the embodimentsthat are illustrated in the various drawing figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation, in the figures of the accompanying drawings and in whichlike reference numerals refer to similar elements.

FIG. 1 is a diagram which illustrates the illumination of a region orpatch of an image plane by a discrete source location.

FIG. 2 is a diagram which illustrates the sampling of a single point inan image plane by multiple discrete source locations.

FIG. 3 is a diagram representing a two-dimensional cross-section ofsubsets of a source comprising an array of discrete source locations anda sensor comprising an array of sensor elements.

FIG. 4 is a diagram representing a possible sampling pattern in an arrayof image pixels within a relatively evenly or well-sampled image plane.

FIG. 5 is a diagram representing a possible sampling pattern in an arrayof image pixels within an image plane wherein rays convergesignificantly.

FIG. 6 is a diagram showing a sensor that is positioned angularly offsetwith respect to a source, the source's alignment being represented by apair of x- and y-axes.

FIG. 7 is a diagram representing the sampling pattern of an image planethat would be generated by an aligned source and sensor, which has worsethan 1 pixel sampling resolution.

FIG. 8 is a diagram representing an image plane wherein the samplingpattern is generated by an angularly offset source and sensor of anembodiment of the present invention.

FIG. 9 is a diagram showing the simulated sampling pattern of a singlepixel within an evenly sampled image plane between an angularly alignedsource and sensor.

FIG. 10 is a diagram showing the simulated sampling pattern of a singlepixel with the sensor being offset relative to the source by 3 degreesin one embodiment of the present invention.

FIG. 11 is a diagram illustrating allocation of sensor data into sourcecoordinate-indexed rows in one embodiment of the present invention.

FIG. 12 is a diagram representing a coordinate-indexed data set of anembodiment of the present invention.

FIG. 13 is a diagram showing a four-segment approximation of an 8×8element sensor of one embodiment of the present invention.

FIG. 14 is a diagram showing a sixteen-segment approximation of anoffset 8×8 element sensor of one embodiment of the present invention.

FIG. 15 is a flow diagram illustrating the incorporation of a segmentapproximation within a separable reconstruction method of one embodimentof the present invention.

FIG. 16 is a diagram illustrating a rectangular, angularly offset sensorthat has been segmented in an approximation method of the presentinvention.

FIG. 17 is a diagram illustrating a segmented model that may be createdfor an angularly offset sensor in one embodiment of the presentinvention.

FIG. 18 is a diagram illustrating a segment approximation of arectangular sensor in one embodiment of the present invention.

FIG. 19 is a diagram illustrating an embodiment of the present inventionwherein two square sensors are positioned to form a rectangular sensoroffset relative to a source.

FIG. 20 is a diagram illustrating an embodiment of the present inventionalso comprising a two-tile sensor.

FIG. 21 is a diagram showing a manner of approximating sensor elementpositions for a two-tile sensor configuration by grouping elements intosegments in one embodiment of the present invention.

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings. While the invention will be described in conjunction withthese embodiments, it will be understood that they are not intended tolimit the invention to these embodiments. On the contrary, the inventionis intended to cover alternatives, modifications and equivalents, whichmay be included within the spirit and scope of the invention as definedby the appended claims. Furthermore, in the following detaileddescription of embodiments of the present invention, numerous specificdetails are set forth in order to provide a thorough understanding ofthe present invention. However, it will be recognized by one of ordinaryskill in the art that the present invention may be practiced withoutthese specific details. In other instances, well-known methods,procedures, components, and circuits have not been described in detailas not to unnecessarily obscure aspects of the embodiments of thepresent invention.

U.S. Pat. No. 5,729,584 entitled “Scanning Beam X-Ray Imaging System,”U.S. Pat. No. 6,876,724 entitled “Large-Area Individually AddressableMulti-Beam X-Ray System and Method of Forming the Same,” both of whichare hereby incorporated by reference, describe X-ray imaging systemsutilizing sources that emit radiation from a plurality of discretelocations on their faces and spatially resolved sensors. These andsimilar imaging systems can acquire sufficient data to reconstructmultiple image planes between the source and sensor and can be usefulfor fluoroscopic guidance, image acquisition for computed tomography,and other applications.

Examples of a source capable of emitting radiation from a plurality ofdiscrete locations may be an array of carbon nanotube cathodes or othernanotube cathodes, scanning electron beam sources, scanning lasersources, and arrays of single cathode emitters.

Spatially resolved sensors in imaging systems of the present inventionmay comprise a sensor array of small sensors or sensor elements, e.g. apixelated detector. A sensor array may comprise elements or pixels ofphoton-counting detectors, energy-integrating detectors,energy-resolving detectors, or any type of detector sensitive to X-rayphotons. A single sensor element or pixel may not be spatially resolved,e.g. the location within an individual sensor element where a photonstrikes may not be recoverable, but a sensor array can be spatiallyresolved by associating data with the position of the sensor element orpixel from which it is received.

FIG. 1 is a diagram which illustrates the illumination of a region orpatch of an image plane by a discrete source location. The diagram ofFIG. 1 illustrates how discrete source location 140 of source 90 canilluminate patch 122 in image plane 280 by emitting rays 102. Afterpassing through an imaging volume, rays 102 are incident on sensor 110.A data set containing the response of elements of sensor 110corresponding to emission by discrete source location 140 may beprocessed or stored in a memory buffer or buffers to be used inconjunction with sensor data corresponding to emissions by otherdiscrete source locations for reconstruction of image plane 280.

FIG. 2 is a diagram which illustrates the sampling of a point in animage plane by multiple discrete source locations and sensor elements,demonstrating how a single point in an image plane may be sampled bymultiple discrete source locations. Plurality of rays 103, all of whichsample point 121, may not be emitted simultaneously but at unique pointsin time, e.g. upon the firing of each discrete source location. Datafrom sensor array 110 corresponding to multiple source locations can besummed and normalized, averaged, or otherwise combined to determineprobable X-ray attenuation properties of point 121. Other points inimage plane 280 can be assigned relative intensity values similarly.

The subsets of discrete source locations and sensor elements whichsample a given point in an image plane, e.g. the discrete sourcelocations that emit and sensor elements that receive plurality of rays103 to sample point 121 in image plane 280, are related to the positionof said image plane between the source and sensor array. While pluralityof rays 103 can be grouped together to reconstruct point 121 in imageplane 280, plurality of rays 103 samples a plurality of different pointsin subsequent image plane 281. Multiple image planes within the spacebetween a source and sensor can be imaged by processing and combiningdata according to ray intersections with the respective planes. Anindividual plane can be selected for viewing, or multiple planes can becombined to provide three-dimensional depth.

A plurality of rays may or may not converge to a point or points insubsequent image plane 281 as rays 103 converged to point 121 in imageplane 280. The convergence seen in plane 280 can actually have negativeeffects for resultant image quality, since rays 103 all sample a singlepoint, providing essentially redundant information, rather than aplurality of points in the image plane which could all contributemeaningful information for the population of image plane with accuratepixel values. The manner in which rays connecting discrete sourcelocations to detector elements converge or fail to converge in variousimage planes can determine the sampling resolution of the system andthereby the accuracy, spatial resolution or quality of resultant images.

Sampling resolution may be characterized as the average number of pointssampled per image pixel. Image pixels can be defined by dividing animage plane into a grid of predetermined dimensions, and taking eachsquare or rectangle of the grid to be an image pixel. Characterizing theaverage number of sample points, e.g. ray intersections, per image pixelrather than total points per image plane may be preferable, as pointsmay not necessarily be distributed evenly within a plane. Having a highsampling resolution, e.g. a number of sampled points within most or allpixels, can be important for a number of reasons. At a minimum, having asampling resolution of at least one point per pixel is necessary toassign a measured value to each pixel in an image. Greater samplingresolution can however be necessary to avoid aliasing or otherdistortions and inaccuracies.

An imaging volume may contain features that are smaller or finer than asingle image pixel; regions within an image pixel may provide varyingamounts of X-ray attenuation. If an image pixel is sampled at only oneor a few points, the value which will be assigned to that pixel mayreflect the properties of the single feature or few features within thepixel that are sampled, which may or may not be a good representation ofthe pixel as a whole. If an image pixel is instead sampled at a largenumber of points, the pixel can be assigned a value based on the averageproperties measured throughout the pixel and likely be a more accuraterepresentation. For example, if an image pixel is mostly X-raytransparent but has a relatively small, X-ray opaque feature, thereconstructed pixel may be assigned a very bright value if it happens tobe sampled only at the small opaque feature. However, if said pixel weresampled at a number of points throughout its area, it may instead beassigned a dim value, representing the average of a small number ofsample points falling on the opaque features and a large number ofsample points falling on the X-ray transparent regions.

Other types of aliasing or prealiasing can occur when samplingresolution is low, particularly when an image has repeating, e.g.sinusoidal, features. The Nyquist criterion for signal processing showsthat the frequency at which a signal is sampled must be at least twicethe frequency of the highest frequency signal component to avoidaliasing, e.g. a type of distortion wherein a high-frequency componentis reconstructed as a relatively lower frequency component. Analogouslyfor image processing, a sampling resolution at least twice as narrow asthe width of the finest features in an image plane may be desirable toavoid aliasing.

Sampling resolution can affect the spatial resolution and fidelity ofreconstructed images. In existing tomosynthetic imaging systems someimage planes tend to have poor sampling resolution due to theconvergence of rays at a small number of sample points.

FIG. 3 is a diagram representing a two-dimensional cross-section ofsubsets of a source comprising an array of discrete source locations anda sensor comprising an array of sensor elements. Source subset 301represents a row of discrete sources such as discrete source 302, andsensor subset 306 represents a row of sensor elements such as sensorelement 307. Rays 303 are emitted by discrete sources and detected bysensor elements 307. There exist planes, e.g. lines in thistwo-dimensional cross-section, between source subset 301 and sensorsubset 306 where little if any convergence exists among rays 303. Forexample, in evenly sampled image plane 304 rays 303 sample a largenumber of well-spaced points in the image plane. However, there alsoexist planes where rays 303 converge and sample relatively few points.For example, in sparsely sampled plane 305 rays 303 converge at pointssuch as convergent point 308, reducing the sampling resolution of theplane. It can be inferred that similar patterns can arise along bothdimensions of a source array and sensor and that there can besignificant variations in sampling resolution between planes in theimaging volume of a tomosynthetic imaging system.

FIG. 4 is a diagram representing a possible sampling pattern in an arrayof image pixels within a relatively evenly or well-sampled image plane.The sampling patterns of pixel array 401 comprises sample points such assample point 405, which represent points at which rays traveling from adiscrete source location to sensor elements intersect said image plane.It can be seen that in pixel array 401 sixteen intersection points occurwithin every pixel. This is equivalent to saying that the samplingresolution in pixel array 401 will be approximately 16 points per pixel,or alternatively quoted per dimension as ¼ of a pixel. The valueassigned to each pixel, e.g. pixel 403, upon image reconstruction may bea weighted sum, average, or other combination of sixteen sample points.

Sampling patterns may be simulated by calculating the center of everysensors in a given array, back-projecting rays from each sensor to anarray of discrete source locations, and recording ray intersectionpoints in a grid of imaging pixels for a selected imaging plane. FIG. 5is a diagram representing a possible sampling pattern in an array ofimage pixels within an image plane wherein rays converge significantly.

In contrast to the relatively populated sampling pattern andquarter-pixel resolution seen in pixel array 401 of FIG. 4, pixel array402 exhibits a sampling resolution of only one pixel. As pixel array 401and pixel array 402 represent image planes or subsets of image planeslocated at different distances between the same source and sensor, itmay be inferred that each sample point within pixel array 402 is sampledby more than one, e.g. sixteen, rays.

The presence and locations of ray convergence points can be related tothe geometry of a tomosynthetic imaging system, namely, to the relativepositions of discrete source locations and sensor elements. Since thesampling pattern in an image plane is created by the intersection ofrays connecting discrete source locations with sensor elements, changingposition parameters of source locations or sensor elements can changethe sampling patterns of each image plane. Referencing FIG. 3 forexample, changing the spacing between discrete sources in source subset301 may change the distances from source subset 301 at which evenlysampled plane 304 or sparsely sampled plane 305 are located. Changingthe spacing between sensor elements in sensor subset 306 may also affectthe locations of evenly or well-sampled and sparsely sampled planes.

Embodiments of the present invention provide manners of improving thesampling resolution of tomosynthetic imaging systems.

In one embodiment of the present invention, a sensor array is angularlyoffset such that x- and y-axes of the sensor, defined for the presentembodiment as axes to which rows and columns, respectively, of sensorelements run parallel, are not angularly aligned with the x- and y-axesof a source, to which rows and columns, respectively, of discrete sourcelocations run parallel. FIG. 6 is a diagram showing a sensor that ispositioned angularly offset with respect to a source, the source'salignment being represented by a pair of x- and y-axes. X-axis 505 andy-axis 506 represent the directions of rows and columns of discreteemissive locations on a source face, respectively. Offset x-axis 503 andoffset y-axis 504 align with rows and columns of sensor face 501. Inthis embodiment of the present invention, the axes of sensor face 501are not angularly aligned with x-axis 505 and y-axis 506; rows andcolumns of the sensor are not angularly aligned with rows and columns ofthe source.

An effect of having an angular offset between the source and sensor inthis embodiment may be to separate rays which would otherwise converge,e.g. that would sample the same point if the source and sensor werealigned. FIG. 7 is a diagram representing the sampling pattern of animage plane that would be generated by an aligned source and sensor,which has worse than 1 pixel sampling resolution. FIG. 8 is a diagramrepresenting the same image plane as FIG. 7, but where the samplingpattern is generated by an angularly offset source and sensor of anembodiment of the present invention. In the embodiment of FIG. 8 aneven, well-populated sampling of the image plane is achieved; samplingresolution is approximately ⅕ of a pixel, a significant increase fromthe sampling resolution of this plane generated by an aligned source andsensor as shown in FIG. 7.

Angularly offsetting a sensor array can alleviate sampling redundancynot only in very sparsely sampled planes but also in image planes whereany amount of ray convergence exists; offsetting a sensor by apredetermined amount does not merely shift points of convergence amongdifferent image planes in the same way that changing the spacing ofsource locations or sensor elements may but can improve samplingresolution throughout the imaging space of a system.

FIG. 9 is a diagram showing the simulated sampling pattern of a singlepixel within an evenly sampled image plane between an angularly alignedsource and sensor. Additional parameters of the simulation included adistance between source and sensor arrays being 1.5 meters and thespacing of sensors in the sensor array, e.g. center-to-center distances,being 0.114 cm. If the pixel of FIG. 9 is representative of other pixelsin its image plane, the sampling resolution of the plane may beapproximately ⅕ of a pixel.

FIG. 10 is a diagram showing the simulated sampling pattern of the samesingle pixel as FIG. 9 but with the sensor being offset relative to thesource by 3 degrees. The increased number of sampling points in thepattern of FIG. 10 suggests that some amount of sampling redundancy,e.g. ray convergence, may have been present in the sampling patternshown in FIG. 9 despite the pixel being relatively well sampled.Simulations can show that in one embodiment of the present invention, a3 degree sensor offset may improve imaging resolution to approximately1/9 of a pixel, or by 80% relative to a non-rotated configuration, in agiven plane between source and sensor. It can also be shown for the sameparameters that other planes between source and sensor also haveimproved sampling resolutions.

Angular offsets between a source and sensor array in embodiments of thepresent invention are not limited to 3 degrees or any other number ofdegrees. An offset may be any number of degrees between 0 and 360degrees. Angular offsets in embodiments of the present invention mayfurther be between 0 and 90 degrees, 0 and 45 degrees, 0 and 30 degrees,0 and 20 degrees, 0 and 10 degrees, or 0 and 5 degrees, inclusive. Forexample, an angular offset may be 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, or 15 degrees. Angular offsets need not be integer number ofdegrees and may be rational or irrational fractions of degrees, such asless than 1 degree, between 1 and 2 degrees, between 2 and 3 degrees,between 3 and 4 degrees, between 4 and 5 degrees, or any otherfractional number of degrees. For example, an angular offset may be anynumber of degrees, including zero, plus or minus ⅛, 1/7, ⅙, ⅕, ¼, ⅓, ½ adegree, or other fractional or decimal numbers of degrees.

However, there may be angular offsets that do not yield spatialresolution benefits, particularly if the sensor has some amount ofrotational symmetry. For example, for a square sensor array, or anyother sensor array with 4-fold rotational symmetry, an angular offset ofninety degrees or any multiple of ninety degrees may recreate the samesampling scenario as a non-offset sensor. For a rectangular sensorarray, or any other sensor array with 2-fold rotational symmetry, anangular offset of 180 degrees or any multiple of 180 degrees mayrecreate the same sampling scenario as a non-offset sensor array.Rotating a sensor array by an angle which is rotationally symmetric to anon-angularly offset sensor array, e.g. rotating a sensor array ofn-fold rotational symmetry by an angle of 360/n degrees, may not resultin spatial resolution benefits.

Amounts of angular offset in embodiments of the present invention mayalso be characterized as a number of “elements per full length” of thesensor. “Elements per full length” may refer to the fractional or wholenumber of sensor elements or pixels by which a corner of the sensor isdisplaced, e.g. vertically or horizontally, from its non-offsetposition. For example, a counterclockwise sensor angular offset maydisplace the upper right corner of the sensor array upwards verticallyand leftward horizontally. The absolute difference between its initialvertical position and its offset vertical position may be divided by theheight of sensor elements to yield a fractional or whole number ofsensor elements per full length, or the absolute difference between itsinitial horizontal position and its offset horizontal position may bedivided by the width of a sensor elements to yield a fractional or wholenumber of sensor elements per full length. This manner ofcharacterization may be particularly useful due to the relationshipbetween sampling patterns and geometries of the source and sensor,specifically, to the size and spacing of discrete emissive locations ona source or elements on a sensor face.

Angular offsets in embodiments of the present invention can be any wholeor fractional number of elements per full length, including by less thanone element per full length. An optimal degree of sensor angular offsetor rotation, e.g. a number of elements per full length that results inthe best sampling resolution, may be an integer number of elements perfull length of the sensor. For example, in one embodiment of the presentinvention, a sensor is rotated by one sensor element per full length ofthe array, and in another embodiment, two elements per full length ofthe sensor array. Both of these embodiments may exhibit optimizedsampling performance. Other integer angular offsets of 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 14, 15, or any other integer number of elements per fulllength of the sensor can be utilized. Alternatively, a sensor array maybe offset by fractional, non-integer numbers of elements per fulllength, including but not limited to 1/16, ⅛, ¼, ⅓, ½, ⅔, or ¾ of anindividual sensor element, or any other fraction of a sensor elementless than, greater than, or between the enumerated values.

Small angles of offset, e.g. small numbers of elements per full length,may utilize available x-ray radiation efficiently; unless an x-raysource or the collimator of an x-ray source is designed for a specificdegree of sensor array offset, positioning a sensor array out ofalignment with the source may result in some sensor elements being movedout of the paths of X-ray beams into space where no X-rays will bereceived. For small angular offsets, e.g. 1, 2, or 3 elements per fulllength, the benefits of improved sampling may be greater than theselosses. For relatively large angular offsets, the decrease in elementsthat will be illuminated by X-ray radiation may become more significant.

In another embodiment of the present invention, a sensor is fabricatedwith vertical and horizontal offsets between sensor elements along rowsand columns, respectively, and utilized for imaging in conjunction witha non-offset source. Vertical and horizontal offsets may be less thanthe length of one sensor element, and the resultant configuration ofsensor elements may be similar to that of a square or rectangular sensorthat has been angularly offset by some amount. In an alternativeembodiment of the present invention, a source is fabricated withvertical and horizontal offsets between discreet emissive locationsalong rows and columns, respectively, and utilized for imaging inconjunction with a non-offset sensor. Either of these embodiments of thepresent invention can improve sampling resolution by creating an angularoffset between the directions of rows and columns on a source andsensor.

The benefits of maintaining an angular offset between a source andsensor in embodiments of the present invention may be attributable tothe creation of a finer sampling “grid” from an increase in the numberof points at which projections of the source array of discrete emissivelocations and sensor array of elements or pixels intersect. This effectmay be visualized by projecting two square grid patterns, representingthe centers of elements of the source and sensor arrays, onto a wall orother surface, and sliding one grid horizontally across the other inincrements of approximately one grid square. If the intersection pointsof the two grids are marked at each increment first for the case wherethe axes of the two grids are parallel and secondly for the case wherethe grid being slid has been rotated by a small degree with respect tothe stationary grid, a larger number of intersection points between thetwo grids for the angularly offset case is visible, demonstrating animprovement of vertical resolution. The same process may be repeatedsliding one grid vertically to demonstrate an improvement in horizontalresolution.

Existing image reconstruction methods may be insufficient to quicklyhandle data from a system utilizing an angularly offset sensor andrealize the image reconstruction-quality benefits of an offset sensorarray. Apart from slightly more complex geometry, back-projection of theviews taken from an angularly offset sensor array onto a focal-planeimage, e.g. the assignment of sensor data to points in an image plane,may not be much more conceptually difficult than back-projection ofviews from a non-offset sensor; rays may be traced from sensor elementsback to discrete source locations and intersection points in a givenimage plane determined.

In one embodiment of the present invention, images are reconstructed bygeometrical back projections of each sensor datum, e.g. the response orvalue of each sensor element upon illumination by each discrete sourcelocation, into the image plane. In this embodiment, the non-parallelgeometry of an imaging system with an angular offset between the sourceand sensor is accounted for during preliminary steps of a rayback-projection method. In this embodiment, inputs such as the locationsof sensor elements on a sensor, e.g. in sensor x-y coordinates, and theangular offset between the source and sensor can be utilized to generatea grid representing offset locations of sensor elements, e.g. in sourcex-y coordinates.

The generation of a coordinate grid representing offset positions ofsensor elements can also be completed using inputs such as predeterminedsensor element spacing, e.g. center-to-center distance, sensordimensions, and the angular offset. Appropriate sensor coordinates canbe calculated from given inputs in any one of a number of ways,including but not limited to application of trigonometric relations,such as sine and cosine, to the distance of an element from thegeometric center of the sensor array and the angular offset; simulationof the offset sensor array and sampling of sensor locations; or anyother method. Rays can be back-projected from the coordinate grid,through image planes to discrete source locations, to determineintersection points with the planes. Monte Carlo or analytical methodsmay or may not be used to simulate interactions of the rays within theimaging volume and calculate probable attenuation properties of themedium based on sensor data in order to assign pixel values within theimage planes.

However, efficient implementations of image plane reconstruction thatcan support real-time image reconstruction may process rows and columnsof sensor array data to be reconstructed independently, in successivepipelined stages. One such implementation is described in U.S. Pat. No.6,178,223 entitled “Image reconstruction method and apparatus” issued toSolomon et al, herein incorporated by reference in its entirety.

Efficient reconstruction methods may process or map data from a sensordata set along one dimension as it is received but process or map thedata along the second dimension following a predetermined amount of dataaccumulation or aggregation. These methods can reduce the amount ofmemory required for storing unprocessed data, e.g. by processing in onedimension as the data is received, while also reducing the overallamount of processing that occurs, e.g. by strategically aggregating datafor further processing.

A set of sensor data can be generated for the firing of each discretesource location. As illustrated in FIG. 1, a discrete source locationcan illuminate a portion or “patch” of an image plane to which acorresponding sensor data set can be mapped. Each data set can beprocessed or mapped along a first dimension, e.g. along its rows, as itis received. For simplicity, rows will be considered to be along ahorizontal direction of the image plane and columns along a verticaldirection. Row-processing a data set can comprise performing anoperation on each sensor datum along a row which maps its horizontalcoordinate or index into a horizontal coordinate of the image plane, andtherefore into an appropriate image pixel column. When the source andsensor are aligned the operation relating a horizontal coordinates of asensor datum to a horizontal image plane coordinate may be a scalingfactor. Scaling factors may be related to the distance between thesource and image plane or between the sensor and image plane and to thehorizontal position, e.g. column, of the sensor element.

Hardware, firmware, or software components can be configured to applyappropriate scaling factors, or mapping coefficients, along each row.Sets of mapping coefficients can be calculated in real time based on theposition of the plane being reconstructed and passed to row processorsor may be stored in the row processors or external memory. One or moreof these row processors can be utilized to row process each data set.When the source and sensor are aligned, the same set of mappingcoefficients may be applied to every row of a given sensor data set asevery row in the data set corresponds to the same set of horizontalcoordinates along the sensor.

After row processing, data may be stored in the form of “pseudo-rows,”rows associated with sensor element rows but populated with data thathas been mapped into the image plane and thereby allocated into imagepixel columns. The number of image pixel columns in a pseudo-row may befewer than the number of columns in the original sensor data set.Pseudo-rows may later be column-processed to complete mapping of thedata into a final image. A pseudo-row or number of pseudo-rows from agiven data set may be combined or grouped with pseudo-rows from otherdata sets prior to column processing. Column processing can comprisesimilar operations as row-processing, where column processors can mapvertical sensor coordinates associated with each pseudo-row intocoordinates of the image plane and allocate the pseudo-rows into imagepixel rows.

This type of method may be termed “separable reconstruction” because themapping of rows and columns of sensor data into respective rows andcolumns of image pixels are separable processes. Namely, a sensor dataset can be row-processed, e.g. mapped pseudo-rows comprising imagepixel-indexed columns, by applying the same set of mapping coefficientsto every row; the row processor does not need to identify whichsensor-indexed row it is processing to apply correct horizontal mappingcoefficients. Similarly, column processing can map entire pseudo-rowsinto image pixel-indexed rows, e.g. into a final image, by applying avertical scaling factor to every element or column across a pseudo-rowor rows; the column processor does not need to identify a sensor columnfrom which image pixel-indexed information was derived in order to applycorrect vertical mapping coefficients across a pseudo-row.

Positioning a sensor array out of alignment with the array of sourcelocations in embodiments of the present invention may break the patternregularities, e.g. the scaling factor relationships between elements ofa sensor data set and a final image plane, that make separablereconstruction possible. When an angular offset exists between a sourceand sensor, mapping sensor data along sensor rows into an image planecan require applying both column-specific scaling factors as before butalso row-specific offsets. Similarly, mapping sensor data into an imageplane along sensor columns can entail applying row-specific scalingfactors as well as a column-specific offsets. A reconstruction methodfollowing that which was previously described may accurately processrows of the sensor data set by providing a row processor for each row ofsensor containing mapping coefficients that comprise both scalingfactors and offsets. However, applying correct column-specific offsetsduring column processing would be impossible since no sense of sensorcolumns exists once data has been mapped into pseudo-rows. Furtherembodiments of the present invention provide manners in which thebenefits of an angularly offset sensor may be incurred withoutsacrificing the potential to optimize efficiency in imagereconstruction.

In one embodiment of the present invention, information sufficient forindependent row and column processing may be maintained for separablereconstruction by altering the structure of the sensor data set prior toor during row or column processing. In this embodiment, rows of a sensordata set can be associated with unique y-coordinates of the source, e.g.relative to a y-axis that is aligned with columns of discrete sourcelocations, rather than with the physical rows of elements along asensor. These “coordinate-indexed” rows may have empty or non-populatedcolumns; each row may contain data in columns only where a sensorelement shares the row's unique y-coordinate. Forming data sets ofcoordinate-indexed rows in this manner can remove the need for applyingcolumn-dependent offsets during columns processing, the offsets beingessentially incorporated into the structure of the data set, and therebyenable an implementation of separable reconstruction.

FIG. 11 is a diagram illustrating allocation of sensor data into sourcecoordinate-indexed rows in one embodiment of the present invention. FIG.11 represents a 4×4 array of sensor elements, where sensor rows arelabeled SR1 through SR4 and sensor columns are labeled SC1 through SC4.Elements are labeled D1 through D16. The y-axis shown in FIG. 11 may bereferenced to columns of a source array. Since the sensor of thisembodiment is offset relative to the source, sensor elements D1 throughD16 are positioned at a plurality of unique positions along this axis,labeled here as Y1 through Y16.

In systems where rows and columns of a source and sensor are angularlyaligned rows and columns of a sensor data set may correspond to rows andcolumns of the sensor array; if the sensor of FIG. 11 was not offsetrelative to a source, it may be convenient to allocate sensor data in a4×4 matrix where rows were indexed SR1 through SR4 and columns whereindexed SC1 through SC4. However, for reasons previously described thistype of data set cannot be utilized for separable reconstruction wherean angular offset exists. In this embodiment of the present invention,data from the sensor array is allocated in rows according to the uniquey-positions of sensor elements, Y1 through Y16. FIG. 12 is a diagramrepresenting a coordinate-indexed data set of an embodiment of thepresent invention. FIG. 12 shows the placement of each individual sensordatum, the values associated with each element D1 through D16 of FIG.11, into an appropriate row of a coordinate-indexed data set. Forexample, the datum associated the first sensor element, D1, is allocatedto a row indexed by its unique y-coordinate, Y4. The datum associatedwith the second sensor element, D2, is allocated to a row indexed by itsunique y-coordinate, Y3, and so forth.

The length of coordinate-indexed rows can be constant through a dataset. In one embodiment of the present invention, the length of eachcoordinate-indexed row is equal to the number of columns of sensorelements on the sensor. For example, the data set of FIG. 12 has fourcolumns, corresponding to the four sensor columns SC1 through SC4. Itcan be seen that coordinate-indexed rows in this embodiment may besparsely populated; since only one sensor element, D4, is associatedwith unique y-position Y1, three columns, SC1 through SC3, of thiscoordinate-indexed row are empty.

In one embodiment of the present invention, separable reconstruction canbe implemented using row processors and column processors. Rowprocessors and column processors can be in hardware, firmware, software,or a combination of any of the three. A row processor may exist forevery coordinate-indexed row of a given sensor data set and may containa set of mapping coefficients which can be applied to sensor elementdata populating a given coordinate-indexed row to map that data toappropriate image pixel-indexed columns of a pseudo-row. In thisembodiment, pseudo-rows may also be coordinate-indexed.

Alternatively, a single row processor, or a number of row processorsless than the number of coordinate-indexed rows, may be utilized. Asmemory buffers, e.g. row buffers, may be used to store datacorresponding to a given sensor element and data may be handled in rowprocessors one column, e.g. one element or datum, at a time, a rowprocessor may be switched between buffers and thereby handle data frommultiple sensor elements. A single row processor, or a number of rowprocessors less than the number of virtual rows, may contain a set orsets of mapping coefficients which can be applied to sensor element datapopulating various coordinate-indexed rows and may map these rowelements into image pixel-indexed columns, e.g. into pseudo-rows.Alternatively, an additional processor can calculate appropriate mappingcoefficients, including but not limited to scaling factors and offsets,that should be applied along a given coordinate-indexed row, andtransmit these coefficients to a row processor before or as it processessaid coordinate-indexed row.

Once row processors have processed the coordinate-indexed rows of FIG.12, e.g. mapped datum D1 through D16 into appropriate imagepixel-indexed columns, sixteen coordinate-indexed pseudo-rows may exist.In the previous description of a separable reconstruction method noinformation about the unique y-coordinate configurations of each columncould be recovered once rows had been processed; the sense of sensorcolumns had been lost by the time data was formed into pseudo-rows.However, in this embodiment of the present invention, each pseudo-row isassociated with a unique y-coordinate, so that the y-coordinateinformation required for column processing is readily available. Acolumn processor can contain a mapping coefficient that translates theunique y-coordinate associate with a coordinate-indexed pseudo-row intoa unique y-coordinate of an image plane, distributing it into anappropriate image pixel-indexed row.

A significantly greater number of coordinate-indexed rows thansensor-indexed rows may be generated for a given data set. For example,if a sensor array has m physical rows of n physical columns, angularlyoffsetting it can create n unique y-coordinates per sensor-indexed row,e.g. m*n coordinate-indexed rows. A column processor or processors maytherefore need to process n times the number of rows for an offsetsensor in this embodiment than for a non-offset sensor. Embodiments ofthe present invention which have been described are in no way limited to4×4 element sensors but can be applied to sensors of any number ofelements. For example, the numbers of rows or columns of sensorelements, e.g. the values of m and n, may be any numbers between 1 and1,000. Thus, the number of coordinate-indexed rows can become quitelarge. In a number of following embodiments of the present invention,predetermined approximations can be made for the x- and y-coordinates ofsensor elements in order to increase the number of populated elementsper coordinate-indexed row and decrease the number of coordinate-indexedrows to be processed.

In one embodiment determination of mapping coefficients for each sensordatum and the allocation of sensor data into coordinate-indexed rows canbe based on an approximation of a sensor as a segmented array whereinadjacent segments have been shifted horizontally and vertically relativeto one another. The horizontal and vertical shifts between segments canbe related to the amount of angular offset between source and sensor.FIG. 13 is a diagram showing a four-segment approximation of an 8×8element sensor of one embodiment of the present invention. In thisapproximation, sensor elements are grouped into four segments, which areseparated by vertical shift 803 and horizontal shift 804 relative to oneanother. It can be seen that in each sensor-indexed row, e.g.sensor-indexed row 806, two unique y-coordinates are created; sensordata may be allocated into a total of 16 coordinate-indexed rows ratherthan the 64 coordinate-indexed rows that may be utilized in anon-approximate implementation.

While the embodiment of FIG. 13 approximates an offset 8×8 elementsensor, sensors of any even number of elements may be approximated inthe same manner of segmenting and segment-shifting. For example, sensorsof 2×2 elements, 4×4 elements, 16×16 elements, 20×20 elements, 30×30elements, 40×40 elements, 50×50 elements, 60×60 elements, 70×70elements, 80×80 elements, 90×90 elements, 100×100 elements, 110×100elements, 120×120 elements, 130×130 elements, 140×140 elements, 150×150elements, 160×160 elements, 170×170 elements, or any other number ofelements between the enumerated values may be modeled as in theembodiment of FIG. 13.

The amount by which sensor segments are shifted in such an approximationmay be related to the size of the angular offset between the source andsensor and with the number of segments being utilized for theapproximation. More than or fewer than four segments can also be definedfor this type of approximation. FIG. 14 is a diagram showing asixteen-segment approximation of an offset 8×8 element sensor of oneembodiment of the present invention. The embodiment of FIG. 14 mayapproximate a sensor of the same number of elements and with the sameangular offset relative to a source as the embodiment of FIG. 13 but mayprovide for a relatively higher fidelity reconstruction; approximationmodels with higher numbers of segments may better represent rotated orangularly offset. However, 32 coordinate-indexed rows for processing arecreated in the embodiment of FIG. 14 compared to the 16 created in theembodiment of FIG. 13. A number of segments chosen for this type ofapproximation may optimize reconstruction quality given the systemresources and time available for processing.

In embodiments of the present invention, angularly offset sensors may bemodeled with 4, 9, 16, 25, 36, or 49 segments or any number of segmentsbetween 4 and 10,000. The number of segments across a sensor face, e.g.in segment rows, may or may not be equal to the number of segments downa sensor face, e.g. in segment columns. Segments may be square orrectangular. The horizontal and vertical shifts between segments inthese approximations, e.g. horizontal shift 804 and vertical shift 803,may be any number or fraction of sensor elements such as ¼ elements, ½elements, ¾ elements, 1 element, 5/4 elements, 3/2 elements, 7/2elements, 2 elements, and so forth, and any integer or non-integernumber of elements between, above or below the enumerated values.

FIG. 15 is a flow diagram illustrating the incorporation of a segmentapproximation within a separable reconstruction method of one embodimentof the present invention. In FIG. 15, block 191 contains possible stepsfor approximation of a sensor of width, W, and height, H, and offset byan angle, φ, around its geometric center relative to a source. Step 195entails the grouping of all sensor elements into rectangular segments.FIG. 16 is a diagram illustrating a rectangular, angularly offset sensorthat has been segmented as in step 195. Sensor 212 is angularly offsetaround its geometric center 210 from its non-offset position 213. InFIG. 16 sensor elements, which are omitted from the illustration forclarity, of sensor 212 can be grouped into six segments, such as segment214; segment 214 and other segments may comprise any number of elements,for example, a sixth of the elements of the full sensor. Segments may bedenoted by a pair of values, (c, r), where c denotes an order along arow, e.g. the second segment across a row may correspond to c=2, and rdenotes an order along a column, e.g. the second segment down a columnmay correspond to r=2. Thus, segment 214 may be denoted segment (3,2).

Step 196 may entail the determination of the distance along thedirection of sensor element rows, dx(c, r), and the distance along thedirection of sensor element columns, dy(c, r), between the center ofeach segment relative and the geometric center of the sensor. Forexample, in FIG. 16 dx(3,2) and dy(3,2) are indicated. Values for eachsegment of dx(c, r) and dy(c, r) may be determined in any manner, forexample by analytical calculation, considering the number of elements ina segment, element spacing, or other factors; physical measurement; orany combination of the two.

Step 197 may entail the determination, by calculation, measurement, orother method, of the physical displacement along the row, D_(x), andalong the column, D_(y), of a corner of an angularly offset sensorrelative to its position when aligned with the source. For example,D_(x) and D_(y) are shown in FIG. 16 as the distances between a cornerof angularly offset sensor 212 and a corner of aligned position 213. Anx-shift value for a segment approximation, S_(x), can be obtained bydividing D_(x) by half the sensor height, e.g. H/2, and a y-shift valueby dividing D_(y) by half the sensor width, e.g. W/2, in step 198.

Step 196 may be performed before, concurrently with, or after step 197and step 198. In step 199 the displacements of segment centers from thesensor center of a segmented model, dx′(c, r) and dy′(c, r), can becalculated as:dx′(c,r)=dx(c,r)+S _(x) *[dy(c,r)÷H]dy′(c,r)=dy(c,r)+S _(y) *[dx(c,r)÷H]with dx(c, r) and dy(c, r) from step 196 and S_(x) and S_(y) from step198. FIG. 17 is a diagram illustrating a segmented model that may becreated for angularly offset sensor 212 by positioning non-rotatedsegments with center positions given by dx′(c, r) and dy′(c, r).

In the embodiment of FIG. 15, block 192, the allocation of sensorelement data for separable reconstruction, and block 194, processorcreation, can be completed sequentially or concurrently. In block 192sensor elements in a segmented model can be assigned tocoordinate-indexed rows as previously described, e.g. with respect tothe embodiment of FIG. 11 and FIG. 12; step 200 can comprise defining acoordinate-indexed row for each unique y-position created in the sensorapproximation of block 191, and step 201 may comprise associating sensorelement data with appropriate column positions within saidcoordinate-indexed rows. In block 194 horizontal mapping coefficientscan be determined from dx′(c, r) and vertical mapping coefficients canbe determined from dy′(c, r) in step 202 and step 203, respectively. Forexample, the locations of elements in a segmented model can bedetermined from the location of their encompassing segment, [dx′(c, r),dy′(c, r)]. Row processors can be created in step 204 and columnprocessors in step 205. In step 204, a number of row processors equal tothe number of coordinate-indexed rows defined in step 200 may becreated, or a number of row processors less than said number of virtualrows, including one, may be created, as previously described.

An efficient image reconstruction from sensor element data can then beaccomplished in block 193. Coordinate-indexed rows can be processed toform pseudo-rows. If a row processor was created for eachcoordinate-indexed row in step 204, a processor may be applied to eachcoordinate-indexed row, as in step 206. In step 206, eachcoordinate-indexed row may be processed simultaneously, if sufficientcomputing power is available, or sequentially. Alternatively, if alesser number of row processors was created in step 204, theprocessor(s) may be applied to multiple coordinate-indexed rows, e.g.switched between locations in row buffers containing element data, as instep 207. It is possible that block 194 and step 206 may be repeated forsensor data corresponding the each discrete source location prior tostep 208, column processing. Once a predetermined number of data setshave been mapped into pseudo-rows, or at any other time, columnprocessors created in step 205 may be applied to complete the separablereconstruction. Indicated by step 209, the image may be displayed,stored, or otherwise utilized.

Block 191, block 192, and block 194 may be executed at any time before,during, or after image data acquisition. Steps 202 through 208 may berepeated a number of times corresponding to the number of discretesource locations, e.g. number of sensor data sets, that contribute to afinal image. Block 193 and block 194 may also be repeated in order toreconstruct multiple planes, e.g. slices at different distances betweenthe source and sensor. Planes may be displayed independently or overlaidfor depth. Blocks and steps in the embodiment of FIG. 15 may beimplemented in hardware, software, firmware, or any combination thereof.

The parameters and calculations of block 191 may also be considered inthe selection of an optimal amount of angular offset to utilize betweena source and sensor. For example, an angular offset may be utilized forwhich the quantities D_(x) and D_(y), and thus S_(x), S_(y), dx′(c, r),and dy′(c, r) are rational. Embodiments of the present inventioncomprising a sensor offset by an integer number of elements per length,e.g. one, two, or three sensor elements per length, may cause the abovequantities to be rational; a sensor may be offset such that D_(x) orD_(y) equals one, two, three, or another integer or rational number ofsensor elements.

Approximations or models other than the segmented approach that has beendescribed can also be utilized to decrease processing time inembodiments of the present invention. Such approximations or models mayinclude but are not limited to rounding, grouping, or otherwisemanipulating the unique y-coordinates of sensor elements across a sensorrow in embodiments of the present invention in a predetermined fashionto decrease the number of coordinate-indexed rows to be processed.

Increasing the size of a sensor, e.g. increasing the numbers of rows andcolumns of a sensor array, can increase the field of view of an imagingsystem. However, increasing the number of sensor elements can alsoincrease the processing demands of the system, particularly inembodiments of the present invention wherein m*n coordinate-indexed rowscan be created during reconstruction. A rectangular sensor may beutilized to provide a relatively long field of view in one direction anda reasonable but smaller field of view in the other, which can be usefulfor a variety of fluoroscopic procedures. The number ofcoordinate-indexed rows created for reconstruction can be limited bysegment approximations as previously described.

FIG. 18 is a diagram illustrating a segment approximation of arectangular sensor in one embodiment of the present invention. Arectangular sensor may be approximated as having a different number ofsquare segments in its rows than in its columns, as in the embodiment ofFIG. 15, but may also be approximated as having an equal number ofrectangular segments in its rows and columns or in any other manner.

FIG. 19 is a diagram illustrating an embodiment of the present inventionwherein two square sensors are positioned to form a rectangular sensoroffset relative to a source. Both square sensors, or “tiles,” canacquire data during imaging, or a single tile can acquire data. Thisembodiment may provide a relatively long field of view in the directionalong the longer dimension of the rectangular sensor if both tiles areutilized or an equally dimensioned field of view if a single tile isutilized.

FIG. 20 is a diagram illustrating an embodiment of the present inventionalso comprising a two-tile sensor. However, in the embodiment of FIG. 20first tile 161 is translated horizontally relative to the embodiment ofFIG. 19 so that it is positioned at the opposite side of second tile162. Tile 161 is shown to the right of tile 162 since this horizontaltranslation description may capture appropriate vertical tile positionsfor one embodiment of the invention. However, similar embodiments cancomprise two rotated detector tiles in a non-rectangular configurationwith other horizontal and vertical positions relative to one another.The numbering of tiles 161 and 162 in FIG. 20 may be reversed withoutsignificant impact for reconstruction or other aspects.

Both of the embodiments of FIG. 19 and FIG. 20 may incur the benefits ofan increased field of view due to the large surface area of the combinedsensor arrays as well as the benefits of improved sampling resolutionfrom an angular offset between source and sensor. However, theconfiguration of sensor elements in the embodiment of FIG. 20 may allowfor particularly efficient image reconstruction. As previouslydescribed, it may be desirable for a system to be operable in modeswhere only first tile 161 is utilized or only second tile 162 isutilized, as well as a mode where both first tile 161 and second tile162 are utilized. A system may be operated utilizing only a single tileduring a fluoroscopy-guided procedure requiring a relatively small fieldof view, or utilizing both tiles during a fluoroscopy-guided procedurerequiring a relatively large field of view. In the embodiment of FIG.19, the number of sensors per full length by which the rectangular,two-tile sensor array is offset is twice the number of sensors per fulllength by which first tile 161 or second tile 162 is offset. In theembodiment of FIG. 20 the number of sensors per full length by which thefull, two-tile sensor array is offset is the same number of sensors perfull length by which first tile 161 or second tile 162 is angularlyoffset. For example, if first tile 161 or second tile 162 were offset byone sensor element per full sensor length, the two-tile sensor in FIG.19 would be offset by two sensor elements per full length whereas thetwo-tile sensor in FIG. 20 would be offset by one sensor element perfull length. As a result, reconstructing sensor data from the embodimentof FIG. 19 may be handled differently in modes where both tiles areutilized than where a single tile is utilized; a larger number ofcoordinate-indexed rows may be defined and processed when both tiles areutilized than when a single tile is utilized. In the embodiment of FIG.20 the same number of and vertical indices for coordinate-indexed rowsmay be utilized during single- and two-tile reconstructions. In additionto decreasing processing time for the two-tile case relative to theembodiment of FIG. 19, this feature can result in little modificationbeing necessary between reconstruction processes for the one- andtwo-tile case.

An implementation of separable reconstruction from the two-tile sensorconfiguration of the embodiment of FIG. 20 can utilize a segmentedapproximation or be non-approximate. FIG. 21 is a diagram showing amanner of approximating sensor element positions for a two-tile sensorconfiguration by grouping elements into segments in one embodiment ofthe present invention. Separable reconstruction may be implementedaccording to first segment group 181 if only first tile 161 is utilized,to second segment group 182 if only second tile 162 is utilized, or toboth first segment group 181 and second segment group 182 if the full,two-tile sensor is utilized. In FIG. 21, some overlap is shown betweenfirst segment group 181 and second segment group 182. However, inpractice the amount by which the sensor is offset can be very small,e.g. a single sensor element per full length of the sensor or othersmall integer numbers of sensor elements per full length of the sensor,for which little to no overlap between segment groups.

In one embodiment of the present invention, the two-tile sensor of FIG.20 can be incorporate in a cardiac fluoroscopy system. The system mayutilize the two-tile sensor to produce high resolution x-ray video forfull cardiac fluoroscopy, but may utilize only a single tile, e.g. firsttile 161 or second tile 162, to produce high resolution x-ray video forcardiac electrophysiology. The sampling resolution benefits created byan angular offset between source and sensor may be present for bothapplications. The two-tile sensor mode can provide an extended field ofview, and the single-tile sensor mode can expose the patient torelatively less x-ray radiation.

Embodiments of the present invention may comprise tomosynthetic imagingsystems utilizing rotated or angularly offset, multi-element sensors ofany shape or size. Sensors may, but need not, comprise multiple smallersensor arrays or tiles is in the embodiments of FIG. 19 and FIG. 20.

Embodiments of the present invention comprising real-time row-processingand aggregated column processing may be particularly efficient for anillumination pattern that runs across rows of discrete source locations.However, the direction of the scan may be reversed; source locationsalong a column may illuminate the image space sequentially, e.g. top tobottom, before restarting at the beginning of the next column. In thiscase, it may be more efficient to process column data first, e.g. duringthe scan, implementing coordinate-indexed columns and column processors,and handle row processing after a predetermined number of data sets havebeen column-processed. While specific embodiments of the presentinvention may refer to a particular order of row and column processing,the order may be reversed without requiring significant changes to themethod described. Furthermore, the definitions of rows and columns neednot be strictly associated with horizontal or vertical directions. Forexample, rows and columns may be related to the pattern in which sourcelocations illuminate the image space, the order in which data isreceived from the sensor, or a variety of other system parameters.

Reconstruction techniques described above are representative only and donot cover all alternatives techniques or details within. Additionalreconstruction aspects, described for a non-offset sensor but which maybe utilized, can be found in U.S. Pat. No. 6,178,223 issued Jan. 23,2001, entitled “Image Reconstruction Method and Apparatus,” U.S. Pat.No. 5,644,612 issued Jul. 1, 1997 entitled “Image ReconstructionMethods,” U.S. Pat. No. 5,751,785 issued May 12, 1998 entitled “ImageReconstruction Methods,” U.S. Pat. No. 6,181,764 issued Jan. 30, 2001entitled “Image Reconstruction for Wide Depth of Field Images,” all ofwhich are herein incorporated by reference.

The foregoing descriptions of specific embodiments of the presentinvention have been presented for purposes of illustration anddescription. They are not intended to be exhaustive or to limit theinvention to the precise forms disclosed, and many modifications andvariations are possible in light of the above teaching. The embodimentswere chosen and described in order to best explain the principles of theinvention and its practical application, to thereby enable othersskilled in the art to best utilize the invention and various embodimentswith various modifications as are suited to the particular usecontemplated. It is intended that the scope of the invention be definedby the claims appended hereto and their equivalents.

What is claimed is:
 1. An X-ray imaging system comprising: a radiationsource configured to emit radiation from a plurality of discreteemissive locations through an imaging volume, wherein said discreteemissive locations of said radiation source are arrayed in rows andcolumns; a radiation sensor comprising a plurality of sensing elements,wherein said plurality of sensing elements comprises a plurality ofsegments of sensing elements, wherein each of said segments is angularlyoffset around its geometric center so that an angular offset existsbetween said sensing elements and said rows and said columns of saiddiscrete emissive locations; and a processor configured to process andallocate responses of said sensing elements to said radiation from adiscrete emissive location of said discrete emissive locations into arespective memory location.
 2. The X-ray imaging system of claim 1wherein said angular offset is less than 90 degrees.
 3. The X-rayimaging system of claim 1 wherein said angular offset is less than 5degrees.
 4. The X-ray imaging system of claim 1 wherein said segmentscomprise: a first segment comprising columns of sensing elements and atleast one row of sensing elements, and a second segment adjacent to saidfirst segment comprising columns of sensing elements and at least onerow of sensing elements.
 5. The X-ray imaging system of claim 4 whereinsaid columns of said first segment are parallel with said columns ofsaid second segment and wherein a row of said first segment is offsetfrom a row of said second segment along a direction of said columns ofsensing elements.
 6. A method comprising: positioning an object forimaging between a radiation source having rows and columns of discreteemissive locations and a radiation sensor having rows and columns ofsensing elements, wherein said plurality of sensing elements comprises aplurality of sensing elements, each of said segments comprising aplurality of said columns and at least one of said rows, wherein each ofsaid segments is angularly offset around its geometric center so that anangular offset exists between said rows and said columns of said sensingelements and said rows and said columns of said discrete emissivelocations, respectively; illuminating a portion of said object withradiation from one of said discrete emissive locations; and detectingresponses of said sensing elements to said radiation.
 7. The method ofclaim 6 further comprising: allocating said responses into a data setwherein data rows correspond to unique positions along a direction ofcolumns of said discrete emissive locations; and determining mappingcoefficients relating said data set to an image plane.
 8. The method ofclaim 7 further comprising: mapping said data set into image plane rowsalong a first dimension.
 9. The method of claim 8 further comprising:illuminating additional portions of said object sequentially byadditional discrete emissive locations; detecting additional responsesfrom said sensing elements; allocating said additional responses fromsaid sensing elements into additional data sets; mapping said additionaldata sets into said image plane rows along said first dimension;aggregating a predetermined number of said image plane rows; and mappingsaid image plane rows into image plane columns along a second dimension.10. The method of claim 6 wherein said angular offset is less than 90degrees.
 11. The method of claim 6 wherein said angular offset is lessthan 5 degrees.
 12. The method of claim 6 wherein said segmentscomprise: a first segment comprising columns of sensing elements and atleast one row of sensing elements, and a second segment adjacent to saidfirst segment comprising columns of sensing elements and at least onerow of sensing elements, wherein said columns of said first segment areparallel with said columns of said second segment and wherein a row ofsaid first segment is offset from a row of said second segment along adirection of said columns of sensing elements.
 13. A method comprising:positioning a radiation source that has rows and columns of discreteemissive locations; positioning a radiation sensor that has rows andcolumns of sensing elements so that radiation from said radiation sourceis incident on said radiation sensor, wherein said sensing elementscomprises a plurality of segments of sensing elements, wherein each ofsaid segments is angularly offset around its geometric center such thatan angular offset less than 90 degrees exists between said rows and saidcolumns of said discrete emissive locations and said rows and saidcolumns of said sensing elements; illuminating a portion of an imagingvolume with radiation from one of said discrete emissive locations; andrecording responses of each of said sensing elements.
 14. The method ofclaim 13 wherein said angular offset is less than 5 degrees.
 15. Themethod of claim 13 further comprising: sequentially illuminatingadditional portions of said imaging volume by said discrete emissivelocations; recording additional responses of each of said sensingelements; and reconstructing an image plane from said responses and saidadditional responses.
 16. The method of claim 15 further comprising:mapping said responses and said additional responses into said imageplane in a first dimension as said responses and said additionalresponses are received.
 17. The method of claim 16 further comprising:aggregating said responses and said additional responses mapped in saidfirst dimension into subsets; and mapping said subsets into said imageplane in a second dimension.
 18. The method of claim 15 furthercomprising: mapping said responses and said additional responses intosaid image plane as said responses and said additional responses arereceived.
 19. The method of claim 13 wherein said segments comprise: afirst segment comprising columns of sensing elements and at least onerow of sensing elements, and a second segment adjacent to said firstsegment comprising columns of sensing elements and at least one row ofsensing elements, wherein said columns of said first segment areparallel with said columns of said second segment and wherein a row ofsaid first segment is offset from a row of said second segment along adirection of said columns of sensing elements.